Daniel Moreira

Key Skills

Software

AWS SageMaker

OpenCV AI Kit (OAK)

SuperAnnotate

Surge AI

Google Cloud Vertex AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Image

Top Task Types

Bounding Box

Computer Programming Coding

Data Collection

Polygon

Text Summarization

Freelancer Overview

I am an experienced data labeling and AI training specialist with over a year of hands-on involvement in diverse projects across NLP, computer vision, and content moderation. My expertise includes annotating and evaluating text for sentiment analysis, intent detection, and chatbot response quality, as well as labeling images and videos for object detection and classification tasks. I have contributed to projects in healthcare, e-commerce, and autonomous vehicles, ensuring high-quality, consistent, and accurate data annotation. I am proficient with industry-standard tools and workflows, and well-versed in following detailed guidelines to deliver reliable results. My strengths include attention to detail, strong analytical skills, and the ability to quickly adapt to new domains and requirements. I am committed to supporting the development of robust AI systems through precise and thoughtful data labeling.

Labeling Experience

Analysis for detection of production in Supermarket lively

Google Cloud Vertex AIVideoBounding BoxClassification

This project involved video data labeling for the detectioin and classification of production activities within supermarket environments. The primary objective was to annotate video footage to identify and track various products and autonomous vehicles operating in the supermarket, supporting the development of machine learning models for inventory management and automation. Key tasks included drawing bounding boxes around products and vehicles, classifying objects acccording to predefined categories, and ensuring high annotation accuracy. The labeling was performed using Google Cloud Vertex AI, leveraging its advanced tools for efficient and consistent annotation. The project covered over 200 hours of video footage, resulting in the annotation 20000+ individual objects. Rigorous quality assurance protocols were followed, including multi-stage reviews and periodic inter-annotator agreement checks, to maintain data integrity and reliability.

This project involved video data labeling for the detectioin and classification of production activities within supermarket environments. The primary objective was to annotate video footage to identify and track various products and autonomous vehicles operating in the supermarket, supporting the development of machine learning models for inventory management and automation. Key tasks included drawing bounding boxes around products and vehicles, classifying objects acccording to predefined categories, and ensuring high annotation accuracy. The labeling was performed using Google Cloud Vertex AI, leveraging its advanced tools for efficient and consistent annotation. The project covered over 200 hours of video footage, resulting in the annotation 20000+ individual objects. Rigorous quality assurance protocols were followed, including multi-stage reviews and periodic inter-annotator agreement checks, to maintain data integrity and reliability.

2023 - 2023

Education

Work History